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1,191 to 1,200 of 5,040 Results
I2VEdit: First-Frame-Guided Video Editing via Image-to-Video Diffusion Models
Nov 25, 2024 - S-Lab for Advanced Intelligence
Ouyang, Wenqi; Dong, Yi; Yang, Lei; Si, Jianlou; Pan, Xingang, 2024, "I2VEdit: First-Frame-Guided Video Editing via Image-to-Video Diffusion Models", https://doi.org/10.21979/N9/2ZLRYG, DR-NTU (Data), V1
The remarkable generative capabilities of diffusion models have motivated extensive research in both image and video editing. Compared to video editing which faces additional challenges in the time dimension, image editing has witnessed the development of more diverse, high-quali...
Related Data for: Cascaded FSO systems with optical reflecting surfaces
Nov 15, 2024 - Narendra VISHWAKARMA
Vishwakarma, Narendra; Swaminathan, R.; Diamantoulakis, Panagiotis D.; Karagiannidis, George K., 2024, "Related Data for: Cascaded FSO systems with optical reflecting surfaces", https://doi.org/10.21979/N9/WKU9JA, DR-NTU (Data), V1
MATLAB and Python source code the publication title: "Cascaded FSO systems with optical reflecting surfaces" These code will produce the outage probability and Bit error rate plots for the above paper
Cascaded FSO systems with optical reflecting surfaces.rar
Nov 15, 2024 - Related Data for: Cascaded FSO systems with optical reflecting surfaces
RAR Archive - 30.4 KB - MD5: 2061fde1d27f1285a0a860e7520fa6f6
Video Diffusion Models are Training-free Motion Interpreter and Controller
Nov 7, 2024 - S-Lab for Advanced Intelligence
Xiao, Zeqi; Zhou, Yifan; Yang, Shuai; Pan, Xingang, 2024, "Video Diffusion Models are Training-free Motion Interpreter and Controller", https://doi.org/10.21979/N9/HQM313, DR-NTU (Data), V1
Video generation primarily aims to model authentic and customized motion across frames, making understanding and controlling the motion a crucial topic. Most diffusion-based studies on video motion focus on motion customization with training-based paradigms, which, however, deman...
MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders
Oct 23, 2024 - S-Lab for Advanced Intelligence
Jiang, Xueying; Jin, Sheng; Zhang, Xiaoqin; Shao, Ling; Lu, Shijian, 2024, "MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders", https://doi.org/10.21979/N9/5ILJOM, DR-NTU (Data), V1
Monocular 3D object detection aims for precise 3D localization and identification of objects from a single-view image. Despite its recent progress, it often struggles while handling pervasive object occlusions that tend to complicate and degrade the prediction of object dimension...
Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Oct 9, 2024 - Kai Keng ANG
Premchand, Brian; Liang, Liyuan; Kok Soon, Phua; Zhang, Zhuo; Wang, Chuanchu; Guo, Ling; Ang, Jennifer; Koh, Juliana; Yong, Xueyi; Ang, Kai Keng, 2024, "Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring", https://doi.org/10.21979/N9/ZJM6WF, DR-NTU (Data), V1
Dataset comprised EEG and ECG data collected from 40 subjects performing MMIT and CVT Tasks as described in the paper.
CVT_20230802-113549_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 14.0 MB - MD5: e3529e64b92c86a140a9b498dfbbad9c
CVT_20230802-142932_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 14.1 MB - MD5: 32f886ae1ff0bad5e63b0debdb29654d
CVT_20230803-111022_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 14.0 MB - MD5: fc255104a008be31c3cd9e76fa4c2c85
CVT_20230803-144900_NeeuroSenze_1.cnt
Oct 9, 2024 - Related Data for: Wearable EEG-Based Brain–Computer Interface for Stress Monitoring
Unknown - 14.0 MB - MD5: fc204e3b07c21057a2963fcb73c33e1f
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